Cooperative Institute for Research in the Atmosphere

About: Cooperative Institute for Research in the Atmosphere is a based out in . It is known for research contribution in the topics: Snow & Data assimilation. The organization has 332 authors who have published 997 publications receiving 38835 citations. The organization is also known as: CIRA.

An Objective Satellite-Based Tropical Cyclone Size Climatology

Abstract: Storm-centered infrared (IR) imagery of tropical cyclones (TCs) is related to the 850-hPa mean tangential wind at a radius of 500km (V500) calculated from 6-hourly global numerical analyses for North Atlantic and eastern North Pacific TCs for 1995‐2011. V500 estimates are scaled using the climatological vortex decay rate beyond 500km to estimate the radius of 5kt (1kt 5 0.514ms 21 ) winds (R5) or TC size. A much larger historical record of TC-centered IR imagery (1978‐2011) is then used to estimate TC sizes and form a global TC size climatology. The basin-specific distributions of TC size reveal that, among other things, the eastern North Pacific TC basins have the smallest while western North Pacific have the largest TC size distributions. The life cycle of TC sizes with respect to maximum intensity shows that TC growth characteristics are different among the individual TC basins, with the North Atlantic composites showing continued growth after maximum intensity. Small TCs are generally located at lower latitudes, westward steering, and preferred in seasons when environmental low-level vorticity is suppressed. Large TCs are generally located at higher latitudes, poleward steering, and preferred in enhanced low-level vorticity environments. Postmaximum intensity growth of TCs occurs in regions associated with enhanced baroclinicity and TC recurvature, while those that do not grow much are associated with west movement, erratic storm tracks, and landfall at or near the time of maximum intensity. With respect to climate change, no significant long-term trends are found in the dataset of TC size.

An Operational Statistical Typhoon Intensity Prediction Scheme for the Western North Pacific

Abstract: The current version of the Statistical Typhoon Intensity Prediction Scheme (STIPS) used operationally at the Joint Typhoon Warning Center (JTWC) to provide 12-hourly tropical cyclone intensity guidance through day 5 is documented. STIPS is a multiple linear regression model. It was developed using a “perfect prog” assumption and has a statistical–dynamical framework, which utilizes environmental information obtained from Navy Operational Global Analysis and Prediction System (NOGAPS) analyses and the JTWC historical best track for development. NOGAPS forecast fields are used in real time. A separate version of the model (decay-STIPS) is produced that accounts for the effects of landfall by using an empirical inland decay model. Despite their simplicity, STIPS and decay-STIPS produce skillful intensity forecasts through 4 days, based on a 48-storm verification (July 2003–October 2004). Details of this model’s development and operational performance are presented.

Particulate sulfate ion concentration and SO 2 emission trends in the United States from the early 1990s through 2010

Abstract: . We examined particulate sulfate ion concentrations across the United States from the early 1990s through 2010 using remote/rural data from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network and from early 2000 through 2010 using data from the Environmental Protection Agency's (EPA) urban Chemical Speciation Network (CSN). We also examined measured sulfur dioxide (SO2) emissions from power plants from 1995 through 2010 from the EPA's Acid Rain Program. The 1992–2010 annual mean sulfate concentrations at long-term rural sites in the United States have decreased significantly and fairly consistently across the United States at a rate of −2.7% yr−1 (p

A New Dual-Polarization Radar Rainfall Algorithm: Application in Colorado Precipitation Events

Abstract: The efficacy of dual-polarization radar for quantitative precipitation estimation (QPE) has been demonstrated in a number of previous studies. Specifically, rainfall retrievals using combinations of reflectivity (Zh), differential reflectivity (Zdr), and specific differential phase (Kdp) have advantages over traditional Z‐R methods because more information about the drop size distribution (DSD) and hydrometeor type are available. In addition, dual-polarization-based rain-rate estimators can better account for the presence of ice in the sampling volume. An important issue in dual-polarization rainfall estimation is determining which method to employ for a given set of polarimetric observables. For example, under what circumstances does differential phase information provide superior rain estimates relative to methods using reflectivity and differential reflectivity? AtColoradoStateUniversity(CSU),anoptimizationalgorithmhasbeendevelopedandusedforanumberof years to estimate rainfall based on thresholds of Zh, Zdr, and Kdp. Although the algorithm has demonstrated robust performance in both tropical and midlatitude environments, results have shown that the retrieval is sensitive to the selection of the fixed thresholds. In this study, a new rainfall algorithm is developed using hydrometeor identification (HID) to guide the choice of the particular rainfall estimation algorithm. A separate HID algorithm has been developed primarily to guide the rainfall application with the hydrometeor classes, namely, all rain, mixed precipitation, and all ice. Both the data collected from the S-band Colorado State University‐University of Chicago‐Illinois State Water Survey (CSU‐CHILL) radar and a network of rain gauges are used to evaluate the performance of the new algorithm in mixed rain and hail in Colorado. The evaluation is also performed using an algorithm similar to the one developed for the Joint Polarization Experiment (JPOLE). Results show that the new CSU HID-based algorithm provides good performance for the Colorado case studies presented here.

Optical, physical, and chemical properties of tar balls observed during the Yosemite Aerosol Characterization Study

Abstract: [1] The Yosemite Aerosol Characterization Study of summer 2002 (YACS) occurred during an active fire season in the western United States and provided an opportunity to investigate many unresolved issues related to the radiative effects of biomass burning aerosols. Single particle analysis was performed on field-collected aerosol samples using an array of electron microscopy techniques. Amorphous carbon spheres, or “tar balls,” were present in samples collected during episodes of high particle light scattering coefficients that occurred during the peak of a smoke/haze event. The highest concentrations of light-absorbing carbon from a dual-wavelength aethalometer (λ = 370 and 880 nm) occurred during periods when the particles were predominantly tar balls, indicating they do absorb light in the UV and near-IR range of the solar spectrum. Closure experiments of mass concentrations and light scattering coefficients during periods dominated by tar balls did not require any distinct assumptions of organic carbon molecular weight correction factors, density, or refractive index compared to periods dominated by other types of organic carbon aerosols. Measurements of the hygroscopic behavior of tar balls using an environmental SEM indicate that tar balls do not exhibit deliquescence but do uptake some water at high (∼83%) relative humidity. The ability of tar balls to efficiently scatter and absorb light and to absorb water has important implications for their role in regional haze and climate forcing.